A companion to Mendenhall and Sincichâ s Statistics for Engineering and the Sciences, Sixth Edition, this student resource offers full solutions to all of the odd-numbered exercises.
A companion to Mendenhall and Sincichâ s Statistics for Engineering and the Sciences, Sixth Edition, this student resource offers full solutions to all of the odd-numbered exercises.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
William Mendenhall was a professor emeritus in the Statistics Department and the first chairman of the department at the University of Florida. Dr. Mendenhall published articles in top statistics journals and was a prolific author of statistics textbooks. Terry L. Sincich is an associate professor in the Information Systems Decision Sciences Department at the University of South Florida, where he teaches introductory statistics at the undergraduate level and advanced statistics courses at the doctoral level. He has won numerous teaching awards, including the Kahn Teaching Award and Outstanding Teacher Award. Dr. Sincich is a member of the American Statistical Association and the Decision Sciences Institute. His research interests include applied statistical analysis and statistical modeling.
Inhaltsangabe
Introduction. Descriptive Statistics. Probability. Discrete Random Variables. Continuous Random Variables. Bivariate Probability Distributions and Sampling Distributions. Estimation Using Confidence Intervals. Tests of Hypotheses. Categorical Data Analysis. Simple Linear Regression. Multiple Regression Analysis. Model Building. Principles of Experimental Design. The Analysis of Variance for Designed Experiments. Nonparametric Statistics. Statistical Process and Quality Control. Product and System Reliability.
Introduction. Descriptive Statistics. Probability. Discrete Random Variables. Continuous Random Variables. Bivariate Probability Distributions and Sampling Distributions. Estimation Using Confidence Intervals. Tests of Hypotheses. Categorical Data Analysis. Simple Linear Regression. Multiple Regression Analysis. Model Building. Principles of Experimental Design. The Analysis of Variance for Designed Experiments. Nonparametric Statistics. Statistical Process and Quality Control. Product and System Reliability.
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